Early detection of mechanical damage by continuously monitoring the metallic debris in lubrication oil of various mechanical systems such as aircraft engines, is extremely important for fault diagnosis, maintenance decision-making, and accident prevention. In-line oil debris detection sensors have attracted attention recently because of the advantage of monitoring machine conditions continuously and eliminating some of the laboratory work required in off-line oil sample analysis. However, most oil debris sensors are not only sensitive to metal particles but also susceptible to various noises and vibrations. Therefore, there are two major issues to be addressed in real time oil debris detection. The first issue is how to use an existing sensor to detect the weakest possible debris or particle signals that are concealed in noise, such that quick responses to incipient failures can be achieved. The second is how to eliminate spurious signals caused by vibrations in the sensor working environment such that reliable maintenance decisions can be made.
The size of a particle that can be detected is mainly limited by background noise, while the challenge of eliminating spurious signals lies in their similarity to particle signals. This calls for an effective de-noising approach to address the two issues simultaneously.
Many de-noising techniques have been reported in the literature. Though de-noising has been studied by many researchers in various fields, work on purification of oil debris signal from the collected noisy data with the effects of vibration has not yet been reported in the accessible literature.
A collected oil debris signal is a mixture of several components including intrinsic noise, interfering vibration signals, and possible target oil-debris signals. However, most of the existing de-noising methods focus on the reduction of background Gaussian noise only, and thus cannot be directly applied to purify the collected oil debris signals.
Therefore there is a need for an improved data processing technique, particularly for enhancing in-line oil debris sensor capability.